Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA

Purpose Despite the farm being considered by many as the most suitable level of decision-making and strategic management in agriculture, there is an increasing interest in evaluating agricultural management strategies at the regional level. Recent initiatives attempted to aggregate and generalise farm-level lifecycle inventory (LCI) data and lifecycle impact assessment (LCIA) results to describe the environmental performance of agricultural regions. This article describes our development and application of a regional statistics-based approach for constructing virtual representative farms (VRFs), representing dominant farm types for a given region, as a tool for comparing alternative regional agricultural strategies in contexts of insufficient farm (e.g. LCI) data. Methods Based on statistical sources, we constructed VRFs of the dominant farm types in the largely agricultural region of Brittany, France. Environmental impacts of different agricultural management strategies were estimated at the regional level by modelling the strategies as changes in VRF-based LCIs, calculating LCIAs and extrapolating their mean per-ha impacts to the total land use in the region. Based on this assessment, performed using a regional lifecycle assessment framework, we analysed relative environmental impacts of each management strategy on the region. A strategy-comparison table was built to allow decision makers to understand the potential regional environmental consequences of implementing each strategy. Results and discussion Once VRFs impact assessment results were extrapolated to the regional level, all strategies show environmental impacts per ha similar to those of the baseline, with differences ranging from −15 to +6%. The scenario featuring centralised fodder drying by 50% of cattle farms (50FOD) is the only one featuring surpluses for all products, due to associated cattle diet adjustments including reduced maize silage intake and partial substitution of concentrate feeds. The scenario featuring grass specialisation by all cattle farms (100GRA) shows a large deficit of grassland products, suggesting that a region-wide extensification strategy would not be self-sufficient. Conclusions The method developed enables comparing environmental consequences of region-wide implementation of agricultural strategies, yet, for our case study, it is particularly difficult to identify a “best” one. Nonetheless, the method serves as an initial step for preselecting strategies to investigate at a more detailed level. Prioritisation of a given strategy would likely be based on the environmental pressures considered most pressing by regional decision makers.

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Bibliographic Details
Main Authors: Avadi Tapia, Angel Daniel, Corson, Michael S., Van Der Werf, Hayo M.G.
Format: article biblioteca
Language:eng
Subjects:E90 - Structure agraire, E11 - Économie et politique foncières, F08 - Systèmes et modes de culture, P01 - Conservation de la nature et ressources foncières, U30 - Méthodes de recherche, structure agraire, pratique culturale, agriculture, impact sur l'environnement, utilisation des terres, analyse du cycle de vie, aménagement du paysage, élevage extensif, pâturages, fourrage, modélisation environnementale, modélisation des cultures, développement agricole, développement régional, http://aims.fao.org/aos/agrovoc/c_7193, http://aims.fao.org/aos/agrovoc/c_2018, http://aims.fao.org/aos/agrovoc/c_203, http://aims.fao.org/aos/agrovoc/c_24420, http://aims.fao.org/aos/agrovoc/c_4182, http://aims.fao.org/aos/agrovoc/c_9000105, http://aims.fao.org/aos/agrovoc/c_4186, http://aims.fao.org/aos/agrovoc/c_2764, http://aims.fao.org/aos/agrovoc/c_5626, http://aims.fao.org/aos/agrovoc/c_36108, http://aims.fao.org/aos/agrovoc/c_9000056, http://aims.fao.org/aos/agrovoc/c_9000024, http://aims.fao.org/aos/agrovoc/c_199, http://aims.fao.org/aos/agrovoc/c_6488, http://aims.fao.org/aos/agrovoc/c_3081, http://aims.fao.org/aos/agrovoc/c_1098,
Online Access:http://agritrop.cirad.fr/584180/
http://agritrop.cirad.fr/584180/7/s11367-017-1300-4.pdf
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id dig-cirad-fr-584180
record_format koha
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic E90 - Structure agraire
E11 - Économie et politique foncières
F08 - Systèmes et modes de culture
P01 - Conservation de la nature et ressources foncières
U30 - Méthodes de recherche
structure agraire
pratique culturale
agriculture
impact sur l'environnement
utilisation des terres
analyse du cycle de vie
aménagement du paysage
élevage extensif
pâturages
fourrage
modélisation environnementale
modélisation des cultures
développement agricole
développement régional
http://aims.fao.org/aos/agrovoc/c_7193
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_203
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_4182
http://aims.fao.org/aos/agrovoc/c_9000105
http://aims.fao.org/aos/agrovoc/c_4186
http://aims.fao.org/aos/agrovoc/c_2764
http://aims.fao.org/aos/agrovoc/c_5626
http://aims.fao.org/aos/agrovoc/c_36108
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_199
http://aims.fao.org/aos/agrovoc/c_6488
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_1098
E90 - Structure agraire
E11 - Économie et politique foncières
F08 - Systèmes et modes de culture
P01 - Conservation de la nature et ressources foncières
U30 - Méthodes de recherche
structure agraire
pratique culturale
agriculture
impact sur l'environnement
utilisation des terres
analyse du cycle de vie
aménagement du paysage
élevage extensif
pâturages
fourrage
modélisation environnementale
modélisation des cultures
développement agricole
développement régional
http://aims.fao.org/aos/agrovoc/c_7193
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_203
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_4182
http://aims.fao.org/aos/agrovoc/c_9000105
http://aims.fao.org/aos/agrovoc/c_4186
http://aims.fao.org/aos/agrovoc/c_2764
http://aims.fao.org/aos/agrovoc/c_5626
http://aims.fao.org/aos/agrovoc/c_36108
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_199
http://aims.fao.org/aos/agrovoc/c_6488
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_1098
spellingShingle E90 - Structure agraire
E11 - Économie et politique foncières
F08 - Systèmes et modes de culture
P01 - Conservation de la nature et ressources foncières
U30 - Méthodes de recherche
structure agraire
pratique culturale
agriculture
impact sur l'environnement
utilisation des terres
analyse du cycle de vie
aménagement du paysage
élevage extensif
pâturages
fourrage
modélisation environnementale
modélisation des cultures
développement agricole
développement régional
http://aims.fao.org/aos/agrovoc/c_7193
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_203
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_4182
http://aims.fao.org/aos/agrovoc/c_9000105
http://aims.fao.org/aos/agrovoc/c_4186
http://aims.fao.org/aos/agrovoc/c_2764
http://aims.fao.org/aos/agrovoc/c_5626
http://aims.fao.org/aos/agrovoc/c_36108
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_199
http://aims.fao.org/aos/agrovoc/c_6488
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_1098
E90 - Structure agraire
E11 - Économie et politique foncières
F08 - Systèmes et modes de culture
P01 - Conservation de la nature et ressources foncières
U30 - Méthodes de recherche
structure agraire
pratique culturale
agriculture
impact sur l'environnement
utilisation des terres
analyse du cycle de vie
aménagement du paysage
élevage extensif
pâturages
fourrage
modélisation environnementale
modélisation des cultures
développement agricole
développement régional
http://aims.fao.org/aos/agrovoc/c_7193
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_203
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_4182
http://aims.fao.org/aos/agrovoc/c_9000105
http://aims.fao.org/aos/agrovoc/c_4186
http://aims.fao.org/aos/agrovoc/c_2764
http://aims.fao.org/aos/agrovoc/c_5626
http://aims.fao.org/aos/agrovoc/c_36108
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_199
http://aims.fao.org/aos/agrovoc/c_6488
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_1098
Avadi Tapia, Angel Daniel
Corson, Michael S.
Van Der Werf, Hayo M.G.
Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA
description Purpose Despite the farm being considered by many as the most suitable level of decision-making and strategic management in agriculture, there is an increasing interest in evaluating agricultural management strategies at the regional level. Recent initiatives attempted to aggregate and generalise farm-level lifecycle inventory (LCI) data and lifecycle impact assessment (LCIA) results to describe the environmental performance of agricultural regions. This article describes our development and application of a regional statistics-based approach for constructing virtual representative farms (VRFs), representing dominant farm types for a given region, as a tool for comparing alternative regional agricultural strategies in contexts of insufficient farm (e.g. LCI) data. Methods Based on statistical sources, we constructed VRFs of the dominant farm types in the largely agricultural region of Brittany, France. Environmental impacts of different agricultural management strategies were estimated at the regional level by modelling the strategies as changes in VRF-based LCIs, calculating LCIAs and extrapolating their mean per-ha impacts to the total land use in the region. Based on this assessment, performed using a regional lifecycle assessment framework, we analysed relative environmental impacts of each management strategy on the region. A strategy-comparison table was built to allow decision makers to understand the potential regional environmental consequences of implementing each strategy. Results and discussion Once VRFs impact assessment results were extrapolated to the regional level, all strategies show environmental impacts per ha similar to those of the baseline, with differences ranging from −15 to +6%. The scenario featuring centralised fodder drying by 50% of cattle farms (50FOD) is the only one featuring surpluses for all products, due to associated cattle diet adjustments including reduced maize silage intake and partial substitution of concentrate feeds. The scenario featuring grass specialisation by all cattle farms (100GRA) shows a large deficit of grassland products, suggesting that a region-wide extensification strategy would not be self-sufficient. Conclusions The method developed enables comparing environmental consequences of region-wide implementation of agricultural strategies, yet, for our case study, it is particularly difficult to identify a “best” one. Nonetheless, the method serves as an initial step for preselecting strategies to investigate at a more detailed level. Prioritisation of a given strategy would likely be based on the environmental pressures considered most pressing by regional decision makers.
format article
topic_facet E90 - Structure agraire
E11 - Économie et politique foncières
F08 - Systèmes et modes de culture
P01 - Conservation de la nature et ressources foncières
U30 - Méthodes de recherche
structure agraire
pratique culturale
agriculture
impact sur l'environnement
utilisation des terres
analyse du cycle de vie
aménagement du paysage
élevage extensif
pâturages
fourrage
modélisation environnementale
modélisation des cultures
développement agricole
développement régional
http://aims.fao.org/aos/agrovoc/c_7193
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_203
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_4182
http://aims.fao.org/aos/agrovoc/c_9000105
http://aims.fao.org/aos/agrovoc/c_4186
http://aims.fao.org/aos/agrovoc/c_2764
http://aims.fao.org/aos/agrovoc/c_5626
http://aims.fao.org/aos/agrovoc/c_36108
http://aims.fao.org/aos/agrovoc/c_9000056
http://aims.fao.org/aos/agrovoc/c_9000024
http://aims.fao.org/aos/agrovoc/c_199
http://aims.fao.org/aos/agrovoc/c_6488
http://aims.fao.org/aos/agrovoc/c_3081
http://aims.fao.org/aos/agrovoc/c_1098
author Avadi Tapia, Angel Daniel
Corson, Michael S.
Van Der Werf, Hayo M.G.
author_facet Avadi Tapia, Angel Daniel
Corson, Michael S.
Van Der Werf, Hayo M.G.
author_sort Avadi Tapia, Angel Daniel
title Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA
title_short Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA
title_full Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA
title_fullStr Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA
title_full_unstemmed Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA
title_sort modelling environmental effects of selected agricultural management strategies with regional statistically based screening lca
url http://agritrop.cirad.fr/584180/
http://agritrop.cirad.fr/584180/7/s11367-017-1300-4.pdf
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AT corsonmichaels modellingenvironmentaleffectsofselectedagriculturalmanagementstrategieswithregionalstatisticallybasedscreeninglca
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spelling dig-cirad-fr-5841802024-01-29T00:15:07Z http://agritrop.cirad.fr/584180/ http://agritrop.cirad.fr/584180/ Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA. Avadi Tapia Angel Daniel, Corson Michael S., Van Der Werf Hayo M.G.. 2018. International Journal of Life Cycle Assessment, 23 (1) : 12-25.https://doi.org/10.1007/s11367-017-1300-4 <https://doi.org/10.1007/s11367-017-1300-4> Modelling environmental effects of selected agricultural management strategies with regional statistically based screening LCA Avadi Tapia, Angel Daniel Corson, Michael S. Van Der Werf, Hayo M.G. eng 2018 International Journal of Life Cycle Assessment E90 - Structure agraire E11 - Économie et politique foncières F08 - Systèmes et modes de culture P01 - Conservation de la nature et ressources foncières U30 - Méthodes de recherche structure agraire pratique culturale agriculture impact sur l'environnement utilisation des terres analyse du cycle de vie aménagement du paysage élevage extensif pâturages fourrage modélisation environnementale modélisation des cultures développement agricole développement régional http://aims.fao.org/aos/agrovoc/c_7193 http://aims.fao.org/aos/agrovoc/c_2018 http://aims.fao.org/aos/agrovoc/c_203 http://aims.fao.org/aos/agrovoc/c_24420 http://aims.fao.org/aos/agrovoc/c_4182 http://aims.fao.org/aos/agrovoc/c_9000105 http://aims.fao.org/aos/agrovoc/c_4186 http://aims.fao.org/aos/agrovoc/c_2764 http://aims.fao.org/aos/agrovoc/c_5626 http://aims.fao.org/aos/agrovoc/c_36108 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_199 http://aims.fao.org/aos/agrovoc/c_6488 France Bretagne http://aims.fao.org/aos/agrovoc/c_3081 http://aims.fao.org/aos/agrovoc/c_1098 Purpose Despite the farm being considered by many as the most suitable level of decision-making and strategic management in agriculture, there is an increasing interest in evaluating agricultural management strategies at the regional level. Recent initiatives attempted to aggregate and generalise farm-level lifecycle inventory (LCI) data and lifecycle impact assessment (LCIA) results to describe the environmental performance of agricultural regions. This article describes our development and application of a regional statistics-based approach for constructing virtual representative farms (VRFs), representing dominant farm types for a given region, as a tool for comparing alternative regional agricultural strategies in contexts of insufficient farm (e.g. LCI) data. Methods Based on statistical sources, we constructed VRFs of the dominant farm types in the largely agricultural region of Brittany, France. Environmental impacts of different agricultural management strategies were estimated at the regional level by modelling the strategies as changes in VRF-based LCIs, calculating LCIAs and extrapolating their mean per-ha impacts to the total land use in the region. Based on this assessment, performed using a regional lifecycle assessment framework, we analysed relative environmental impacts of each management strategy on the region. A strategy-comparison table was built to allow decision makers to understand the potential regional environmental consequences of implementing each strategy. Results and discussion Once VRFs impact assessment results were extrapolated to the regional level, all strategies show environmental impacts per ha similar to those of the baseline, with differences ranging from −15 to +6%. The scenario featuring centralised fodder drying by 50% of cattle farms (50FOD) is the only one featuring surpluses for all products, due to associated cattle diet adjustments including reduced maize silage intake and partial substitution of concentrate feeds. The scenario featuring grass specialisation by all cattle farms (100GRA) shows a large deficit of grassland products, suggesting that a region-wide extensification strategy would not be self-sufficient. Conclusions The method developed enables comparing environmental consequences of region-wide implementation of agricultural strategies, yet, for our case study, it is particularly difficult to identify a “best” one. Nonetheless, the method serves as an initial step for preselecting strategies to investigate at a more detailed level. Prioritisation of a given strategy would likely be based on the environmental pressures considered most pressing by regional decision makers. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/584180/7/s11367-017-1300-4.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1007/s11367-017-1300-4 10.1007/s11367-017-1300-4 info:eu-repo/semantics/altIdentifier/doi/10.1007/s11367-017-1300-4 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/s11367-017-1300-4 info:eu-repo/grantAgreement/EC/FP7/289328//(EU) Crops and ANimals TOGETHER/CANTOGETHER